Adaptive PPO With Multi-Armed Bandit Clipping and Meta-Control for Robust Power Grid Operation Under Adversarial Attacks by Mohamed Massaoudi, Katherine R. Davis

“…The simulation results validate that CePPO&#x2019;s adaptive parameter tuning and enhanced exploration strategies make it particularly well-suited for the dynamic nature of power grid control. To foster further research and reproducibility, the code is available upon request at <uri>https://github.com/Dr-Kate-Davis-s-Research-Team/DRL-CP.S</uri>…”
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Spilt Tensile Strength of Fiber-Reinforced Recycled Aggregate Concrete Simulation Employing Tunned Random Forests Trees by Xiao Chen, Chen Xi, Min Xiao, Lang Wu

“…A data set including 257 data points and 10 input variables was taken from peer-reviewed published research and arbitrarily split into three phases: testing, validating, and training. …”
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Combating electricity fraud: Employing hybrid learning and computer vision for sustainable energy management by Jui-Sheng Chou, Nader Anwar Charaf, Dani Nugraha Limantono, Hoang-Minh Nguyen

“…This research aims to develop AI models for automatically detecting electricity fraud, helping utility companies minimize financial losses and ensure a more resilient and sustainable energy system.…”
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An explainable AI-based blood cell classification using optimized convolutional neural network by Oahidul Islam, Md Assaduzzaman, Md Zahid Hasan

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Utilization of Deep Learning YOLO V9 for Identification and Classification of Toraja Buffalo Breeds by Abdul Rachman Manga', Herawati Herawati, Purnawansyah Purnawansyah

“…In response to the need for an accurate and efficient identification method, this research utilizes the YOLOv9 (You Only Look Once version 9) deep learning model to detect and classify Toraja buffalo breeds. …”
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Self-adaptive evolutionary neural networks for high-precision short-term electric load forecasting by Muhammad Abbas, Yanbo Che, Sarmad Maqsood, Muhammad Zain Yousaf, Mustafa Abdullah, Wajid Khan, Saqib Khalid, Mohit Bajaj, Mohammad Shabaz

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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…The 1000 kV dry-type air-core shunt reactor, as one of the key components of ultra-high voltage AC transmission systems, is still in the preliminary stage of research regarding its grading ring configuration. …”
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Predicting high-need high-cost pediatric hospitalized patients in China based on machine learning methods by Peng Zhang, Bifan Zhu, Xing Chen, Linan Wang

“…The programs targeting existing HNHC patients have shown limited long-term impact, and research predicting HNHC pediatric patients in China is limited. …”
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Accurate modeling and simulation of the effect of bacterial growth on the pH of culture media using artificial intelligence approaches by Suleiman Ibrahim Mohammad, Hamza Abu Owida, Asokan Vasudevan, Suhas Ballal, Shaker Al-Hasnaawei, Subhashree Ray, Naveen Chandra Talniya, Aashna Sinha, Vatsal Jain, Ahmad Abumalek

“…Abstract This research investigates the impact of bacterial growth on the pH of culture media, emphasizing its significance in microbiological and biotechnological applications. …”
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Fractal Neural Network Approach for Analyzing Satellite Images by Volodymyr Shymanskyi, Oleh Ratinskiy, Nataliya Shakhovska

“…The neural network models were trained and tested with varying hyperparameters, including learning rates and batch sizes. …”
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Instagram fake profile detection using an ensemble learning method by Bharti Goyal, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, Piyush Kumar Shukla, Shreyas J

“…We investigate and provide a solution to the issue of Instagram’s ability to identify phony accounts in this research. An F1 score of 98%, a recall of 98%, a precision of 98.3%, and an accuracy of 98.24% are all achieved by the new, perfectly accurate model that is used in the proposed research. …”
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A U-net based reconstruction of high-fidelity simulation results for flow around a ship hull based on low-fidelity inviscid flow simulation by Dayeon Kim, Jeongbeom Seo, Inwon Lee

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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…Fake audio detection, a critical technology in modern digital security, addresses the growing threat of manipulated audio content across various applications, including media, legal evidence, and cybersecurity. This research proposes a novel transfer learning approach for fake audio detection. …”
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Transfer learning for predicting of gross domestic product growth based on remittance inflows using RNN-LSTM hybrid model: a case study of The Gambia by Haruna Jallow, Ronald Waweru Mwangi, Alieu Gibba, Herbert Imboga

“…This paper addresses a critical research gap by employing artificial intelligence (AI) techniques to forecast GDP based on remittance inflows.…”
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The application of artificial intelligence models in predicting the risk of diabetic foot: a multicenter study by Yao Li, Siyuan Zhou, Bichen Ren, Shuai Ju, Xiaoyan Li, Wenqiang Li, Bingzhe Li, Yunmin Cai, Chunlei Chang, Lihong Huang, Zhihui Dong

“…Early identification of high-risk DF patients can reduce disability and mortality. The research also aims to create an integrated application to assist clinicians in precise, efficient risk assessment for early intervention. …”
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Advanced machine learning for innovative drug discovery by Igor V. Tetko, Djork-Arné Clevert

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HCAP: Hybrid cyber attack prediction model for securing healthcare applications. by Mohanad Faeq Ali, Mohammed Shakir Mohmood, Ban Salman Shukur, Rex Bacarra, Jamil Abedalrahim Jamil Alsayaydeh, Masrullizam Mat Ibrahim, Safarudin Gazali Herawan

“…Addressing these challenges requires advanced cybersecurity measures to protect the dynamic IoMT ecosystem from evolving threats. This research focuses on enhancing cyberattack prediction and prevention in IoMT environments through innovative Machine-learning techniques to improve healthcare data security and resilience. …”
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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

“…By incorporating SHapley Additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), the research introduces interpretability to enhance model transparency. …”
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Test Case Prioritization Based on Neural Networks Classification: A Replication Study and Hyper-Parameter Optimization Using Taguchi Methods by Andreea Vescan, Cristina-Maria Tiutin

“…Running all test cases would be time-consuming, however, Test Case Prioritization (TCP) could help in this direction by ordering the execution of test cases considering various criteria, for example, fault detection and time constraint. This research aims to achieve two main objectives: the first is to replicate the experiments outlined in the original article, and the second is to determine the optimal hyperparameters for existing AI models, with a particular focus on neural networks. …”
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Study on an interpretable prediction model for pile bearing capacity based on SHAP and BP neural networks by Shunbo Li, Mingwei Hai, Qi Zhang, Bin Zhou, Miao Wang, Zhuo Zhao

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